Streaming Data Architectures: Processing Streaming Data

Overview/Description
Expected Duration
Lesson Objectives
Course Number
Expertise Level

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Overview/Description
Process streaming data with Spark, the analytic engine built on Hadoop. In this course, you will discover how to develop applications in Spark to work with streaming data and generate output. Topics include the following: Configure a streaming data source; Use Netcat and write applications to process the data stream; Learn the effects of using the Update mode on your stream processing application's output; Write a monitoring application that listens for new files added to a directory; Compare the append output with the update mode; Develop applications to limit files processed in each trigger; Use Spark's Complete mode for output; Perform aggregation operations on streaming data with the DataFrame API; Process streaming data with Spark SQL queries.

Expected Duration (hours)
0.9

Lesson Objectives

Streaming Data Architectures: Processing Streaming Data

Course Overview

install the latest available version of PySpark

configure a streaming data source using Netcat and write an application to process the stream

describe the effects of using the Update mode for the output of your stream processing application

write an application to listen for new files being added to a directory and process them as soon as they come in

compare the Append output to the Update mode and distinguish between the two

develop applications that limit the files processed in each trigger and use Spark's Complete mode for the output

perform aggregation operations on streaming data using the DataFrame API

work with Spark SQL in order to process streaming data using SQL queries

define and apply standard, re-usable transformations for streaming data

recall they key ways to use Spark for streaming data and explore the ways to process streams and generate output

Course Number:
it_dssdardj_02_enus

Expertise Level
Intermediate